scholarly journals DEVELOPING A DATA FUSION STRATEGY BETWEEN OMNIDIRECTIONAL IMAGE AND INDOORGML DATA

2019 ◽  
Vol XLII-4/W19 ◽  
pp. 117-124
Author(s):  
A. R. C. Claridades ◽  
D. Ahn ◽  
J. Lee
Keyword(s):  
Data Conversion ◽  
Position Information ◽  
Indoor Location ◽  
Indoor Space ◽  
3D Space ◽  
Experimental Implementation ◽  
Omnidirectional Image ◽  
Omnidirectional Images ◽  
Relationship Of ◽  
Topological Data

Abstract. As the interest in indoor spaces increases, there is a growing need for indoor spatial applications. As these spaces grow in complexity and size, research is being carried out towards effective and efficient representation. Omnidirectional images give a snapshot of interiors and give visually rich content, but only contain pixel data. For it to be used in providing indoor services, its limitations must be overcome. First, the images must be connected to each other to represent indoor space continuously based on spatial relationships that may be provided by topological data. Second, the objects and spaces that we see in these images must also be recognized. This paper presents a study on how to link omnidirectional images and an IndoorGML data without the need for data conversion, provision of reference data, or use of different data models in order to provide Indoor Location-Based Service (LBS). We introduce the use of the Spatial Extended Point (SEP) to characterize the relationship between the omnidirectional image and the topological data. Position information of the object is used to define a region of 3D space, to determine the inclusion relationship of an IndoorGML node. We conduct an experimental implementation of the integrated data in the form of a 3D Virtual Tour. The connection of the Omnidirectional images is demonstrated by a visualization of navigation through a hallway towards a room’s interior delivered to the user through a clicking action on the image.

scholarly journals Development of an Omnidirectional-Image-Based Data Model through Extending the IndoorGML Concept to an Indoor Patrol Service

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Hyo-jin Jung ◽  
Jiyeong Lee
Keyword(s):  
Data Model ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Indoor Location ◽  
Indoor Space ◽  
Omnidirectional Image ◽  
Space Data ◽  
Omnidirectional Images ◽  
Indoor Spaces ◽  
Topological Data

Different indoor representation methods have been studied for their ability to provide indoor location-based services (LBS). Among them, omnidirectional imaging is one of the most typical and simple methods for representing an indoor space. However, a georeferenced omnidirectional image cannot be used for simple attribute searches, spatial queries, and spatial awareness analyses. To perform these functions, topological data are needed to define the features of and spatial relationships among spatial objects including indoor spaces as well as facilities like CCTV cameras considered in patrol service applications. Therefore, this study proposes an indoor space application data model for an indoor patrol service that can implement functions suited to linking indoor space data and service objects. In order to do this, the study presents a method for linking data between omnidirectional images representing indoor spaces and topological data on indoor spaces based on the concept of IndoorGML. Also, we conduct an experimental implementation of the integrated 3D indoor navigation model for patrol service using GIS data. Based on the results, we evaluate the benefits of using such a 3D data fusion method that integrates omnidirectional images with vector-based topological data models based on IndoorGML for providing indoor LBS in built environments.

scholarly journals Integrating Image and Network-Based Topological Data through Spatial Data Fusion for Indoor Location-Based Services

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Dasol Ahn ◽  
Alexis Richard C. Claridades ◽  
Jiyeong Lee
Keyword(s):  
Data Fusion ◽  
Spatial Data ◽  
Urban Areas ◽  
Spatial Information ◽  
Indoor Navigation ◽  
Location Based Services ◽  
Data Conversion ◽  
Position Information ◽  
Indoor Space ◽  
Topological Data

Nowadays, the importance and utilization of spatial information are recognized. Particularly in urban areas, the demand for indoor spatial information draws attention and most commonly requires high-precision 3D data. However accurate, most methodologies present problems in construction cost and ease of updating. Images are accessible and are useful to express indoor space, but pixel data cannot be applied directly to provide indoor services. A network-based topological data gives information about the spatial relationships of the spaces depicted by the image, as well as enables recognition of these spaces and the objects contained within. In this paper, we present a data fusion methodology between image data and a network-based topological data, without the need for data conversion, use of a reference data, or a separate data model. Using the concept of a Spatial Extended Point (SEP), we implement this methodology to establish a correspondence between omnidirectional images and IndoorGML data to provide an indoor spatial service. The proposed algorithm used position information identified by a user in the image to define a 3D region to be used to distinguish correspondence with the IndoorGML and indoor POI data. We experiment with a corridor-type indoor space and construct an indoor navigation platform.

scholarly journals Indoor path visualization method based on the spatial characteristics of indoor environment

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Jiafeng Shi ◽  
Jie Shen ◽  
Zdeněk Stachoň ◽  
Yawei Chen
Keyword(s):  
Indoor Environment ◽  
Design Method ◽  
Three Dimensional ◽  
Indoor Environments ◽  
Route Guidance ◽  
Visualization Method ◽  
Continuous Space ◽  
Indoor Location ◽  
Indoor Space ◽  
Map Design

<p><strong>Abstract.</strong> With the increasing number of large buildings and more frequent indoor activities, indoor location-based service has expanded. Due to the complicated internal passages of large public buildings and the three-dimensional interlacing, it is difficult for users to quickly reach the destination, the demand of indoor paths visualization increases. Isikdag (2013), Zhang Shaoping (2017), Huang Kejia (2018) provided navigation services for users based on path planning algorithm. In terms of indoor path visualization, Nossum (2011) proposed a “Tubes” map design method, which superimposed the channel information of different floors on the same plane by simplifying the indoor corridor and the room. Lorenz et al (2013) focused on map perspective (2D/3D) and landmarks, developed and investigated cartographic methods for effective route guidance in indoor environments. Holscher et al (2007) emphasized using the landmark objects at the important decision points of the route in indoor map design. The existing studies mainly focused on two-dimensional plane to visualize the indoor path, lacking the analysis of three-dimensional connectivity in indoor space, which makes the intuitiveness and interactivity of path visualization greatly compromised. Therefore, it is difficult to satisfy the wayfinding requirements of the indoor multi-layer continuous space. In order to solve this problem, this paper aims to study the characteristics of the indoor environment and propose a path visualization method. The following questions are addressed in this study: 1) What are the key characteristics of the indoor environment compared to the outdoor space? 2) How to visualize the indoor paths to satisfy the users’ wayfinding needs?</p>

scholarly journals BIM-BASED INDOOR PATH PLANNING CONSIDERING OBSTACLES

2017 ◽  
Vol IV-2/W4 ◽  
pp. 417-423 ◽  
Author(s):  
M. Xu ◽  
S. Wei ◽  
S. Zlatanova ◽  
R. Zhang
Keyword(s):  
Path Planning ◽  
Semantic Information ◽  
Indoor Navigation ◽  
Triangular Prism ◽  
Building Structures ◽  
Indoor Space ◽  
Space Subdivision ◽  
3D Space ◽  
Building Components ◽  
2D And 3D

At present, 87&amp;thinsp;% of people’s activities are in indoor environment; indoor navigation has become a research issue. As the building structures for people’s daily life are more and more complex, many obstacles influence humans’ moving. Therefore it is essential to provide an accurate and efficient indoor path planning. Nowadays there are many challenges and problems in indoor navigation. Most existing path planning approaches are based on 2D plans, pay more attention to the geometric configuration of indoor space, often ignore rich semantic information of building components, and mostly consider simple indoor layout without taking into account the furniture. Addressing the above shortcomings, this paper uses BIM (IFC) as the input data and concentrates on indoor navigation considering obstacles in the multi-floor buildings. After geometric and semantic information are extracted, 2D and 3D space subdivision methods are adopted to build the indoor navigation network and to realize a path planning that avoids obstacles. The 3D space subdivision is based on triangular prism. The two approaches are verified by the experiments.

scholarly journals DEFINING GEOSPATIAL DATA FUSION METHODS BASED ON TOPOLOGICAL RELATIONSHIPS

2018 ◽  
Vol XLII-4/W9 ◽  
pp. 317-319 ◽  
Author(s):  
D. S. Ahn ◽  
J. H. Park ◽  
J. Y. Lee
Keyword(s):  
Data Fusion ◽  
Ground Surface ◽  
Location Based Services ◽  
Geospatial Data ◽  
Data Conversion ◽  
Geospatial Information ◽  
Topological Relationship ◽  
Topological Relationships ◽  
Fusion Methods ◽  
Relationship Of

<p><strong>Abstract.</strong> Currently, geospatial datasets are produced in various models and formats in accordance with the spatial scale of the real world such as ground/ surface/underground or indoor/outdoor. The location-based services application also uses the optimal data model and format for each purpose. Therefore, there are various geospatial dataset for representing features of the same space. Various geospatial data on same object cause problems with the financial problems and the suitability of the data. In the paper, we reviewed how to integrate existing geospatial data to utilize geospatial data constructed in different models and formats. There are four main ways to fuse existing geospatial information. The existing geospatial data fusion methods consist of a method through geometry data conversion, a method through the aspect of visualization, a method based on attribute data, and a method using topological relationships. Based on this review, we defined a geospatial data fusion method on topological relationships, which is a method considering topological relationship between geospatial objects. In this method, the topological relationship of objects uses the basic concept of IndoorGML.</p>

Adapted Approach for Omnidirectional Egomotion Estimation

2013 ◽  
pp. 1-13
Author(s):  
A. Radgui ◽  
C. Demonceaux ◽  
E. Mouaddib ◽  
M. Rziza ◽  
D. Aboutajdine
Keyword(s):  
Optical Flow ◽  
Experimental Results ◽  
Motion Field ◽  
Camera Motion ◽  
Spherical Representation ◽  
Estimation Process ◽  
Error Measures ◽  
Egomotion Estimation ◽  
Omnidirectional Image ◽  
Omnidirectional Images

Egomotion estimation is based principally on the estimation of the optical flow in the image. Recent research has shown that the use of omnidirectional systems with large fields of view allow overcoming the limitation presented in planar-projection imagery in order to address the problem of motion analysis. For omnidirectional images, the 2D motion is often estimated using methods developed for perspective images. This paper adapts motion field calculated using adapted method which takes into account the distortions existing in the omnidirectional image. This 2D motion field is then used as input to the egomotion estimation process using spherical representation of the motion equation. Experimental results are shown and comparison of error measures are given to confirm that succeeded estimation of camera motion will be obtained when using an adapted method to estimate optical flow.

scholarly journals Omnigradient Based Total Variation Minimization for Enhanced Defocus Deblurring of Omnidirectional Images

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yongle Li ◽  
Jingtao Lou
Keyword(s):  
Image Processing ◽  
Imaging Systems ◽  
Total Variation Minimization ◽  
Defocus Blur ◽  
Omnidirectional Imaging ◽  
Gradient Computation ◽  
Omnidirectional Image ◽  
3D Scene ◽  
Omnidirectional Images ◽  
Computing Method

We propose a new method of image restoration for catadioptric defocus blur using omnitotal variation (Omni-TV) minimization based on omnigradient. Catadioptric omnidirectional imaging systems usually consist of conventional cameras and curved mirrors for capturing 360° field of view. The problem of catadioptric omnidirectional imaging defocus blur, which is caused by lens aperture and mirror curvature, becomes more severe when high resolution sensors and large apertures are used. In an omnidirectional image, two points near each other may not be close to one another in the 3D scene. Traditional gradient computation cannot be directly applied to omnidirectional image processing. Thus, omnigradient computing method combined with the characteristics of catadioptric omnidirectional imaging is proposed. Following this Omni-TV minimization is used as the constraint for deconvolution regularization, leading to the restoration of defocus blur in an omnidirectional image to obtain all sharp omnidirectional images. The proposed method is important for improving catadioptric omnidirectional imaging quality and promoting applications in related fields like omnidirectional video and image processing.

scholarly journals INDOOR SPACE LOCATION MODEL BASED ON LOCATION SERVICE

2017 ◽  
Vol XLII-4/W7 ◽  
pp. 49-53
Author(s):  
Y. Zhou ◽  
G. Zeng ◽  
Y. Huang ◽  
X. Yang
Keyword(s):  
Spatial Information ◽  
Indoor Navigation ◽  
Location Model ◽  
Location Information ◽  
Location Based Service ◽  
Location Services ◽  
Indoor Location ◽  
Indoor Space ◽  
Location Service ◽  
Space Model

Location is the basis for the realization of location services, the integrity of the location information and its way of representation in indoor space model directly restricts the quality of location services. The construction of the existing indoor space model is mostly for specific applications and lack of uniform representation of location information. Several geospatial standards have been developed to meet the requirement of the indoor spatial information system, among which CityGML LOD4 and IndoorGML are the most relevant ones for indoor spatial information. However, from the perspective of Location Based Service (LBS), the CityGML LOD4 is more inclined to visualize the indoor space. Although IndoorGML is mainly used for indoor space navigation and has description (such as geometry, topology, and semantics) benefiting for indoor LBS, this standard model lack explicit representation of indoor location information. In this paper, from the perspective of Location Based Service (LBS), based on the IndoorGML standard, an indoor space location model (ISLM) conforming to human cognition is proposed through integration of the geometric and topological and semantic features of the indoor spatial entity. This model has the explicit description of location information which the standard indoor space model of IndoorGML and CityGML LOD4 does not have, which can lay the theoretical foundation for indoor location service such as indoor navigation, indoor routing and location query.

The Contrast Study on the Method of STEP/XML Data Transformation

2011 ◽  
Vol 403-408 ◽  
pp. 4103-4107
Author(s):  
Jian Dong Shang ◽  
Ya Peng Zhang ◽  
Dong Fang Hu
Keyword(s):  
Collaborative Design ◽  
Data Transformation ◽  
Heterogeneous Data ◽  
Data Conversion ◽  
Contrast Study ◽  
Product Model ◽  
Xml Data ◽  
Partial Data ◽  
Relationship Of ◽  
Element Mapping

Heterogeneous data sharing is always a bottleneck problem for the development of collaborative design. The method of STEP/XML element mapping achieves the data transformation between STEP and XML by establishing the mapping relationship of the two data. It’s hard to ensure all element mapping one to one and easy to cause the partial data loss. Based on the research, this paper put forward a new method with data encapsulation. It encapsulates the whole STEP data into the XML data by using of the XML character data, and then the data are uploaded to the collaborative design platform. Another designer can download it and get the original STEP data by using the XML parser. This method is not only easy to be realized, but also can ensure the integrity of the product model data conversion. It is more conducive to achieve collaborative design.

scholarly journals A Simplified CityGML-Based 3D Indoor Space Model for Indoor Applications

2020 ◽  
Vol 10 (20) ◽  
pp. 7218
Author(s):  
Qun Sun ◽  
Xiaoguang Zhou ◽  
Dongyang Hou
Keyword(s):  
Semantic Information ◽  
Indoor Navigation ◽  
Geometric Information ◽  
Indoor Space ◽  
Emergency Rescue ◽  
Interior Spaces ◽  
Topological Relationships ◽  
Building Components ◽  
Relationship Of ◽  
Indoor Spaces

With the continuous development of indoor positioning technology, various indoor applications, such as indoor navigation and emergency rescue, have gradually received widespread attention. Indoor navigation and emergency rescue require access to a variety of indoor space information, such as accurate geometric information, rich semantic information and indoor spatial adjacency information; hence, a suitable 3D indoor model is needed. However, the available models, such as BIM and CityGML, mainly represent geometric and semantic information of indoor spaces, and rarely describe the topological adjacency relationship of interior spaces. To address the requirements of indoor navigation and emergency rescue, a simplified 3D indoor model is proposed in this research. The building components and indoor functional spaces of buildings are described in a simplified way. The geometric and semantic information are described based on CityGML, and the topological relationships of indoor adjacent spaces are represented by CityGML XLinks. While describing the indoor level of detail (LOD) of buildings in detail, the model simplifies building components and indoor spaces, which can preserve the characteristics of indoor spaces to the maximum extent and serve as a basis for indoor applications.

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